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Generative AI is everywhere now. You see it in content, campaigns, customer experiences, and even internal workflows. It promises speed, scale, and efficiency, but there’s a harder question sitting underneath all that progress; Do your audiences actually trust it?

Trust in the Age of AI: What Consumers Really Think About AI Generated Content

Today, PR teams aren’t just tracking media coverage and share of voice. They’re also measuring how their brand shows up in AI-generated answers, search summaries, and large language models (LLMs). This new LLM visibility layer is quickly becoming a critical part of PR performance.

15 Must-Have PR KPIs and How to Track Them

See how one platform can power every decision across PR, communications, and marketing.

The Meltwater Blog

Blog Topics: Generative Engine Optimization, Media Intelligence, Media Relations, Social Listening, Consumer Intelligence, Influencer Marketing

Find out how you can leverage Facebook to boost your brand's online presence and gain a competitive edge. Explore the Meltwater category page today!

Facebook Blog | Meltwater

Find out how you can leverage Instagram to boost your brand's visual appeal and gain a competitive edge. Explore our category page today!

Instagram Blog | Meltwater

Find out how you can leverage LinkedIN to grow your professional network and gain a competitive edge. Explore the Meltwater category page today!

LinkedIn Blog | Meltwater

Find out how you can leverage TikTok to elevate your brand with creative content and gain a competitive edge. Explore the Meltwater category page today!

TikTok Blog | Meltwater

Find out how you can leverage X / Twitter to engage your audience effectively and gain a competitive edge. Explore the Meltwater category page today!

X / Twitter Blog | Meltwater

Find out how you can leverage YouTube to create engaging video content and gain a competitive edge. Explore the Meltwater category page today!

YouTube Blog | Meltwater

Generative Engine Optimization (GEO) is transforming how brands show up in AI-powered search. Explore insights, strategies, and best practices to help your content rank and resonate across conversational engines like ChatGPT, Gemini, and Copilot.

Explore insights and strategies for Generative Engine Optimization (GEO) to help your brand stay visible and discoverable in AI-powered search.

Generative Engine Optimization (GEO) Blog Collection | Meltwater

Every day billions of conversations take place on social media: tweets, posts, comments, blogs, reviews, podcasts, and much more.
Learn how to use social listening to make sense of all of that data.

On our social listening category page, you find all our blogs covering topics around social listening and social media monitoring. Read more.

Social Listening Blogs | Category

Business Reputation Management: What does it take to add reputation management to your marketing strategy? More importantly, how do you keep your reputation sparkly and shiny? Here’s your all-access guide to online reputation management for the long term.

On our reputation management category page, you find all our blogs covering topics around business reputation management. Read more.

Reputation Management Blogs | Category

From your brand's logo to your website, your social media presence to your customer support—these elements combined are what constitutes a brand in the minds of customers. But, there are thousands of other businesses that have a logo, website, social media presence, and website. So, how can you position your business on the market and make it stand out from the competition?
The key to success is branding & brand management!

On our brand management category page, you find all our blogs covering topics around brand management. Build your strategy and reach your goals!

Brand Management Blogs | Category

Competitive intelligence and the act of collecting competitive data can be seen as growth drivers for a company. Our guide will help you understand the concept of competitive intelligence (CI) by answering questions such as: What is the definition of competitive intelligence? How is competitive intelligence useful to organizations? What is the goal of competitive intelligence? And more.

On our competitive intelligence category page, you find all our blogs covering topics around competitive intelligence. Learn how to stay ahead.

Competitive Intelligence Blogs | Category

Let’s dive into the customer journey framework and how to optimize the process by creating a customer journey map and using metrics that matter when analyzing the customer journey.

On our customer journey category page, you find all our blogs covering topics around mapping and understanding the customer journey.

Customer Journey Blogs | Category

What Is Data Analytics? [Beginner’s Guide 2023]
How can I grow my business? 
How do customers interact with my newly launched product?
How do I increase the productivity of my employees?
How do I know if my marketing efforts are working?
We have just two words for you...Data analytics!

On our data analytics category page, you find all our blogs covering topics around AI and data analytics. Technical and still easy to understand.

AI & Data Analytics Blogs | Category

Public relations and media relations can add impact to any marketing strategy. It’s an opportunity for brands to grow their reach beyond traditional sales messages. PR helps to shape the image you want people to have of your brand.
So, what is PR and how do you use it? This guide shows you everything you need to know to build a strong public relations foundation.

On our public relations (PR) category page, you find all our blogs covering public relations and communications topics. Step up your PR game.

Public Relations (PR) Blogs | Category

We all know exactly what the roles of sales or accounting are in a company, right? We might even have a slight idea of what the IT guys are doing.
But there is another business discipline, that plays a crucial role in organizations, even more so during the pandemic – internal communications!
But what exactly do we mean by that, what purpose does it serve and what steps can you take to ensure you and your employees will communicate effectively?

On our internal communications category page, you find all our blogs about internal comms topics. Learn about the intranet, internal newsletters, and more.

Internal Communications Blogs | Category

As the internet has taken root in more areas of our lives — everything from entertainment to shopping to paying bills and more — traditional marketing is becoming less impactful. As any marketer knows, you need to focus on where your audience is if you want to reach them. Since the average person spends about seven hours a day online, it’s no surprise that content has maintained its hold on marketers.

Here's a closer look at what content marketing is and why it matters more than ever in our digital-first economy.

On our content marketing category page, you find blogs about content marketing topics. Learn about strategies, KPIs, tips, and more. Make your content king!

Content Marketing Blogs | Category

The rise of the influencer marketing space – today a $10 billion industry, growing 50% per year – is one of the clearest examples of how social media is transforming traditional marketing. These days having a business website, presence on social, PR coverage, and your own content isn’t enough to compete.
We'll dive into the intricacies of influencer marketing to help ensure that you're equipped with the insights needed to be successful in this space.

On our influencer marketing category page, you find blogs about influencer marketing topics. Build your strategy, find influencers, and measure results.

Influencer Marketing Blogs | Category

Have you just launched a new product or service that you want to get the word out about? Maybe you want to share with consumers why it is awesome and how it is so much better than the one your competitors offer.

Well, then, there is one thing you can't do without...Marketing!

On our marketing category page, you find blogs about marketing topics. Learn about all the different angles and types of marketing and improve your results.

Marketing Blogs | Category

In this guide, we want to give you a peek into the definition of social media management, the daily schedule of a social media manager, social media platforms to promote your business, and the do’s & don’ts of social media management.
Are you ready to begin the journey of becoming a social media superstar?

On our social media management category page, you find blogs about social media management topics. Build and manage your online community.

Social Media Management Blogs | Category

Building a following and using social media platforms to reach a wider audience requires a well-planned social media marketing strategy. In this guide, we’ll be looking at why social media marketing is so essential and how you can make it work for your business.

On our social media marketing category page, you find blogs about social media marketing topics. Learn how to get the highest paid social ROI!

Social Media Marketing Blogs | Category

In the fast-evolving realm of digital marketing and public relations, utilizing the right tools is crucial for success. Our interdisciplinary category showcases all the pertinent tools for digital marketing & PR. These tools help in enhancing your online presence and effectively reaching target groups, whether through reputation management, influencer marketing, or social media management.

On our digital marketing and PR tools category page, you find all our blogs covering topics around mapping and understanding the customer journey.

Digital Marketing & PR Tools Blogs | Category

In this article, we’ll explain why LLM misinformation has become a frontline crisis issue, how misinformation shows up in AI systems, and what you can do about it to safeguard your brand reputation. You will find a practical crisis communications playbook, guidance on prevention and measurement, common mistakes to avoid, and clear answers to the most common questions communications leaders are asking right now. 

Why LLM Misinformation is a Crisis Comms Issue Now

How Misinformation Shows Up in LLMs (and Why it’s Hard to Correct)

A Practical Crisis Comms Playbook for Correcting LLM Misinformation

Prevention: “Pre-bunking” Your Brand Narrative for AI

Brand Safety Measurement: How to Report Progress to Leadership

What Are Common AI Brand Safety Mistakes to Avoid?

How Meltwater Can Help You Spot and Correct LLM Misinformation

For growing numbers of consumers, AI is a convenient first port of call when they’re seeking information and recommendations. When someone asks a chatbot about your company, that answer often forms their first impression before they even visit your website. They may not visit your website at all, if they feel the large language model (LLM) has given them all the details they need. 

A single incorrect sentence about pricing, safety, leadership, or legal status can shape perception at scale in minutes. Unlike traditional media, there is no editor to call and no correction box to negotiate, the answer simply appears, confidently, and moves on.

Misinformation in this context includes hallucinations, which are fabricated details presented as fact, as well as outdated or miscontextualized information that is stitched together from partial sources. These risks are well documented in the AI field, but for communications leaders, the issue is practical, not theoretical. 

PR teams are responsible for protecting trust, managing reputation, and responding to issues before they escalate. AI-generated misinformation cuts across all three.

This becomes a crisis when the misinformation involves executive impersonation, safety or compliance claims, financial or pricing errors, or narratives tied to scandals or litigation. In those moments, AI answers are not just inaccurate. They can be harmful. They can influence investors, regulators, customers, and employees before your team even knows there is a problem. Treating this as an edge case or a future concern leaves your organization exposed.

As AI continues to shape how audiences discover and evaluate brands, AI in brand reputation management will become an essential discipline for safeguarding trust and credibility.

To manage the problem, you need to understand how it happens. Most LLMs generate responses by synthesizing patterns from training data and retrieved sources, but when those sources are outdated, incomplete, or inconsistent, the output reflects those flaws. Missing context is another major driver, because AI systems often compress complex topics into short answers, which increases the risk of oversimplification or distortion.

Misinformation appears in several distinct ways. For example, LLM  outputs can include direct errors or invented details. Search-style generative summaries, such as Google AI Overviews, can blend multiple sources into a single answer that looks authoritative but lacks nuance.

Correction is hard because you are not correcting a single article or post, but attempting to influence a system that draws from many inputs. You cannot force an instant update, although what you can do is increase the likelihood that accurate, authoritative information is retrieved and repeated. 

This requires a different mindset from traditional crisis response.

Step 1: Detect and document (within hours)

Speed matters, the first step is identifying problems early, and that means running a consistent set of prompts that reflect how real people might ask about your brand, executives, products, and industry. When you find an error, capture it carefully, save screenshots, note the prompt used, the date and time, the model or platform, and any cited sources. 

Treat this like evidence gathering, because clear documentation helps you assess severity, coordinate internally, and track whether corrections take hold over time.

Step 2: Classify severity and route internally

Not all misinformation carries the same risk; some errors are inconvenient but low impact, while others demand immediate escalation. 

Legal, financial, medical, or safety-related claims should trigger review by legal and risk teams. Errors about product capabilities or partnerships often require coordination between communications, marketing, and product leaders, while minor biographical or historical inaccuracies still matter, but can usually be handled through standard correction workflows.

Clear severity classification keeps teams aligned and prevents overreaction or delay.

Step 3: Publish the correction where AI systems can trust it

This is the most important step. AI systems tend to rely on sources that are consistent, structured, and clearly authoritative, so use these tips: 

Create or update a central source page on your owned properties that states the correct facts plainly. 

Use clear headings, direct language, timestamps, and citations where appropriate. 

Include a short correction or FAQ section that answers common questions in simple terms.

Consistent entity naming matters, so use the same company, product, and executive names everywhere to reduce ambiguity and help AI systems connect the dots.

Sometimes you just have to create replacement content and wait and hope that LLMs replace it.

Allie Konchar, Partner & Chief Client Officer, Omniscient

Step 4: Amplify with credible third-party validation (earned media)

Owned content alone is not enough, you also need credible earned media that reinforces corrections and increases the chances that AI systems will pick up the right information. When necessary, issue a statement, contribute a byline, or engage with reputable outlets that can explicitly state the corrected facts. 

Specific, factual coverage is more useful than vague reassurance. AI systems latch onto clear assertions backed by trusted publishers.

Tip: Learn more about earned media for GEO, and about earned media monitoring.

Step 5: Platform pathways (what you can and can’t control)

Transparency is essential. Some AI platforms offer feedback or reporting mechanisms, while others do not, so you should use available options, but you should not rely on them alone. When trying to correct errors that consistently appear in popular LLMs, your influence is indirect and cumulative, so it can take time and persistence to resolve the problem.  

Setting expectations internally prevents frustration among stakeholders, and keeps your team focused on what actually works.

Step 6: Monitor, measure, and close the loop

Correction is not complete until you verify results, so be sure to re-run the same prompts on a regular cadence to track whether the incorrect narrative persists, whether sources change, and whether your authoritative content appears. Look for drift, where the core facts are right but framing shifts in subtle ways, and lose the loop by documenting outcomes and refining your approach for next time.

Tip: Use GenAI Lens to automatically benchmark prompt outputs over time, so you can see how your activity is making an impact.

Reactive response is necessary, but prevention is more efficient - think of this as building truth infrastructure. Your About pages, leadership bios, product specifications, and policy statements should be current, detailed, and easy to parse, and you should publish verifiable proof points with dates and primary sources. Avoid vague marketing language when clarity matters.

Apply these principles to how you structure and maintain your content ecosystem, and you’ll build strong foundations which reduce the likelihood of future misinformation.

Leadership wants clarity - this is a complex, emerging discipline and it’s essential to help stakeholders fully understand the nature of the issue as well as the practical steps you can take to achieve the desired results.  

Start by measuring narrative accuracy across a defined set of prompts, then track the percentage of correct versus incorrect answers over time. Measure time to correction, from first detection to observed improvement in AI outputs. Monitor source replacement, noting when unreliable sources are displaced by your authoritative content or credible coverage. Finally, track recurrence. If the same misinformation keeps reappearing, that signals a deeper source issue that needs attention.

These metrics frame AI brand safety as risk management, not experimentation. They help leaders understand progress, prioritize resources, and support proactive investment.

Meltwater’s GenAI Lens is built to manage this process for you - book a demo today to discover how it works.

One common mistake is treating this as a surface-level PR cleanup without fixing the underlying source ecosystem. Another is publishing vague corrections that hedge instead of stating facts clearly, which causes problems because AI systems favor crisp, unambiguous language. Inconsistent naming across pages and platforms also creates confusion that AI systems amplify. Finally, many teams fail to establish a monitoring cadence, which means problems resurface unnoticed.

Misinformation in LLMs occurs when an AI system generates responses that are factually incorrect, misleading, or missing critical context, while presenting them with confidence. This can include fabricated details, outdated information, or distorted summaries that misrepresent reality.

AI brand safety is the practice of protecting your brand’s reputation and trust when AI systems generate, summarize, or rank information about your organization. It focuses on preventing, detecting, and correcting inaccurate or harmful AI-generated narratives.

Why is LLM misinformation a crisis communications issue?

LLM misinformation is a crisis issue because AI answers often serve as a first impression and spread without friction. Errors can influence stakeholders quickly and quietly, leaving communications teams little time to respond if they are not prepared.

How do I know if an LLM is spreading misinformation about my brand?

You know by actively testing. Run regular prompts related to your brand, products, and leaders across major AI systems. Monitor responses for accuracy, tone, and sourcing, and document any errors you find.

What’s the fastest way to correct AI-generated misinformation?

The fastest effective approach is to publish a clear correction on an authoritative owned page and reinforce it with credible earned media. This improves the likelihood that AI systems retrieve and repeat the correct information.

Can companies directly “fix” what ChatGPT or other LLMs say?

Companies cannot directly edit responses in most consumer AI systems. What you can do is influence future outputs by improving the quality, clarity, and authority of the sources those systems rely on.

Does earned media help correct misinformation in AI answers?

Yes. Credible earned media helps because AI systems often trust established outlets. Coverage that clearly states corrected facts increases the chance that future AI outputs reflect those facts.

How long does it take for corrections to show up in AI outputs?

Timelines vary. Some changes appear in days or weeks, others take longer. It depends on the system, the sources involved, and how widely the corrected information is published and referenced.

How should crisis teams monitor AI search and chatbots ongoing?

Teams should establish a regular prompt-testing cadence, track changes over time, and integrate AI monitoring into existing crisis and brand safety workflows rather than treating it as a separate task.

What should be published on our website to reduce future LLM misinformation?

Publish clear, current, and well-structured pages that state facts plainly. Maintain consistent naming, include dates and sources, and update content regularly to signal reliability.

Managing AI-driven misinformation requires visibility. GenAI Lens gives communications teams that visibility by showing how brands are represented across major AI systems and where those narratives originate. You can see which sources AI systems cite, how sentiment and framing shift, and where inaccuracies emerge. That insight helps you act faster and with more precision.

GenAI Lens connects AI narratives to earned, owned, and paid media performance, so you can align correction efforts with a broader communications strategy. Combined with Meltwater’s monitoring, analytics, and reporting capabilities, teams can detect issues early, publish authoritative corrections, and track whether those corrections hold. Brands like Heineken use Meltwater to maintain clarity and consistency in complex global narratives, demonstrating how strong intelligence supports confident action.

AI has changed how information spreads. Brand safety now depends on how well you manage truth in systems you do not control. With the right visibility, processes, and tools, you can correct misinformation, protect trust, and stay ahead of the narrative in the AI era.

Brand Safety in the AI Era: How to Correct Misinformation in Chatbots and AI Search

Every year, people around the world ring in January 1 with the goal of getting in shape. However, this almost cliché resolution has a new twist in the 2020s. Internet users can now ask LLM models, like ChatGPT and Google AI Overview, which digital tools can best help them get fit.

For marketers, this is part of an important shift: LLMs are reshaping the customer journey. Understanding how they interpret authority and user intent to generate recommendations consumers trust is now a must-have capability for competitive brands. 

So, what are these AI-powered helpers telling consumers? We used GenAI Lens, Meltwater’s industry-first LLM tracker, to find out. 

Our analysis of the top LLM recommendations for fitness apps during two critical weeks — the end of 2025 and start of 2026 — focuses on how this new facet of brand discovery is influencing the customer journey. Read on to discover the brands, sources, keywords, and more that dominated this year’s New Year’s resolution season.

Note: The data below comes from our GenAI Lens analysis of responses from nine LLM models — Anthropic Claude, ChatGPT, Deepseek, Google AI Mode, Google AI Overviews, Google Gemini, Meta Llama, Perplexity, and xAI Grok— from December 24, 2025, to January 7, 2026. Click here to learn more about how GenAI Lens helps major global brands decode, monitor, and impact their LLM visibility.

Our GenAI Lens analysis found that Strava was the most visible brand in LLM recommendations for effective fitness apps. 

From December 24, 2025, to January 7, 2026, LLMs mentioned Strava 138 times in response to the prompt “What are the most effective fitness apps to get in shape?” Additionally, Strava achieved a GenAI Lens Prevalence Score of 70%, meaning it appeared in 70% of the resulting responses. Those metrics along with an analysis of prominence within answers resulted in a 77% Visibility Score for the popular running app.

MyFitnessPal was Strava’s closest competitor, with a higher volume of mentions but lower prevalence, resulting in a Visibility Score of 71%. Meanwhile, Fitbod and Nike Training Club, or NTC, followed with Prevalence Scores of 61% and 55%, respectively.

Takeaway: LLM visibility doesn’t only rest on how many times your brand is mentioned. Prevalence, or how widespread your mentions are, can make or break your standing against competitors.

How Does User Intent Impact LLM Recommendations?

The language LLMs used in their responses to the prompt “What are the most effective fitness apps to get in shape?” highlights how their interpretation of effectiveness prioritized strength-building, approach, and progress tracking. For example, the keyword "strength" (75% visibility) appeared more often than other qualities related to effectiveness, like “stamina” or “endurance”, which were absent. 

"Equipment", a key factor in deciding on which workouts to try, also achieved relatively high visibility at 45%. Finally, keywords more generally related to advancement, like "progress" (38% visibility), also appeared.

Together, the top keywords highlight how the LLM models relate fitness app effectiveness to strength. But what if the user has other qualities, like efficiency, in mind when on the hunt for the best fitness app? 

To learn more about how LLM recommendations vary as user intent changes, we also analyzed responses to the prompt “What are the best fitness apps for quick routines?”

Our GenAI Lens analysis found that FitOn was the top brand in LLM recommendations for fitness apps for quick workouts, with a Visibility Score of 76%. NTC was the second-ranked fitness app recommended for quick routines with an average Visibility Score of 53%. Meanwhile, the top fitness app for effectiveness, Strava — which many users love for showing off long runs — understandably sank to 35th place with only 10% visibility. 

Contrasting with LLM recommendations for effective fitness apps, "equipment" (185 mentions) was the top keyword in responses to our prompt for quick routines. Meanwhile, "strength" (128 mentions) dropped to third place after "quick routines" (169 mentions).

Takeaway: User intent shapes how LLMs recommend and talk about brands. For marketers, this means understanding LLMs portray your brand generally and in relation to specific consumer needs. Tools like GenAI Lens let you monitor prompt variations and responses at scale, giving you a dynamic, panoramic view of your brand’s LLM presence.

How Do LLM Responses Differ from One Another?

Our GenAI Lens analysis found that fitness app visibility varies drastically between LLM models.
In AI-generated recommendations for effective fitness apps, Strava was the most consistently visible brand, with a 77% Visibility Score overall. However, that score dipped as low as 17% on Google Gemini and as high as 99% on Google AI Overviews. 

Fitbod (which ranked third in overall visibility) scored higher than any other app on ChatGPT and Google AI Overviews, two top targets for many consumer brands. And notably, most of the brands that appeared in responses from the top LLMs were nowhere to be found on Meta Llama. 

Takeaway: While high visibility across all of the top LLMs is ideal, refining strategies to target specific models can help brands more effectively reach their target audiences. GenAI Lens breaks down visibility by channel, allowing marketers to zero in on new opportunities and identify low-hanging fruit. 

Garage Gym Reviews was the top source cited in LLM recommendations of effective fitness apps, according to GenAI Lens. Its dedicated, site-wide focus on comparative fitness reviews helped make it a highly influential LLM source on the topic of fitness apps. Top URLs referenced were best-workout-apps (88 mentions), best-free-workout-apps (27 mentions), and best-personal-training-apps (17 mentions), highlighting AI’s reliance on authoritative, ranking-style content when surfacing recommendations.

Interestingly, the second-ranked source, Die Ringe, was the only fitness app brand website to make the list. The website for the German calisthenics app was mentioned 55 times in LLM recommendations, seemingly stemming from the prominence of self-referencing, user-generated reviews on its homepage. However, that visibility did not translate into LLMs recommending the app itself. 

Finally, YouTube and Reddit came in third and fourth, respectively, powered by the kind of unfiltered, peer reviews that LLMs lean on. For example, the most referenced Reddit thread was “What’s the best automated workout app?”, posted in the r/bodyweightfitness subreddit in June 2023. Its 663 engagement actions in a highly active community likely pushed LLM models to favor it as an authoritative source, even despite its age.

Takeaway: Niche websites and digital communities with high authority and engagement can have outsized impacts on LLM recommendations. Meanwhile, brands that host authentic user reviews prominently on their own websites can also become trusted sources for generative AI models. 

What Fitness Brands Need to Know About LLM Recommendations

Our GenAI Lens analysis of AI recommendations for fitness apps revealed both the dominant brands, as well as the forces behind their visibility. In a nutshell:

Brand visibility in LLM recommendations depends on both volume and prevalence of brand mentions.

Look at user intent, as expressed through subtle shifts in language, for a fuller picture of how your brand is portrayed to audiences as they go on their “prompt journeys”.

Brands with high visibility on one LLM can be completely absent on another. Understanding LLM response variations is key to building strategies that focus on reaching your target audiences where they are. 

LLMs rely on sources with both expert and peer-led expertise, even if they are old. Generally, comparative reviews, like ranking lists, and UGC, like starred reviews, are paramount. 

LLM recommendations are key aspects of the shopping experience for high-intent buyers. Brands across consumer sectors must monitor and analyze them rigorously to remain competitive, but doing so is impossible without the right tools. GenAI Lens is here to help. Fill out the form below to request a sneak peek at how this industry-leading technology can take your brand’s LLM strategy to new heights.

Which fitness apps were most recommended by LLMs for effectiveness in early 2026?

According to GenAI Lens data, Strava ranked first with a 77% Visibility Score. MyFitnessPal followed with a 71% Visibility Score, despite higher mention volume but lower prevalence. Fitbod and Nike Training Club ranked next with 61% and 55% prevalence, respectively.

What workout qualities do LLMs associate with “effective” fitness apps?

A GenAI Lens analysis of LLM responses to the prompt “What are the most effective fitness apps to get in shape?” found that they mentioned “strength” most, followed by “workouts”, “apps”, “equipment”, and “progress”. 

How do LLM recommendations change when users ask for quick workouts instead?

Meltwater’s GenAI Lens analysis of responses to “best fitness apps for quick routines” found that FitOn ranked first with a 76% Visibility Score, while Nike Training Club ranked second at 53% visibility. Strava dropped to 35th place with just 10% visibility, despite being recommended most in prompts for effective fitness apps, illustrating how shifts in user intent drastically reshape AI recommendations.

Do AI-generated recommendations vary across LLM models?

Yes. A Meltwater GenAI Lens analysis of fitness app recommendations found that Strava’s overall 77% Visibility Score ranged from 99% on Google AI Overviews to just 17% on Google Gemini. Fitbod achieved its highest visibility on ChatGPT and Google AI Overviews, while several top-ranking brands were completely absent from Meta Llama responses.

Which sources most influence LLM fitness app recommendations?

Meltwater GenAI Lens analysis of fitness app recommendations found that Garage Gym Reviews ranked as the most cited source, with 88 mentions of its best-workout-apps page, 27 mentions of best-free-workout-apps, and 17 mentions of best-personal-training-apps. Other top sources included PC Mag, Wired, Tom’s Guide, YouTube, and Reddit.

Does old content impact LLM recommendations?

Yes. In Meltwater’s GenAI Lens analysis of fitness app recommendations, the most referenced Reddit thread — “What’s the best automated workout app?” from June 2023 — accumulated 663 engagement actions in the r/bodyweightfitness subreddit. Despite being over two years old, its engagement and community authority elevated it as a trusted LLM source.

Can brand websites influence LLM responses?

Yes. In Meltwater’s GenAI Lens analysis of fitness app recommendations, Die Ringe, a German calisthenics app, ranked second among cited sources with 55 mentions, driven by prominent self-hosted user reviews. However, despite high source visibility, the app itself was not consistently recommended, underscoring the difference between source authority and brand recommendation.

How does GenAI Lens help brands improve LLM visibility?

Meltwater’s  GenAI Lens tracks mention volume, prevalence, visibility score, keyword associations, source citations, and LLM-specific performance across models. This enables brands to identify gaps — such as low visibility on ChatGPT or Google AI Overviews — and optimize content, reviews, and PR strategies accordingly.

Fitness Apps Brand AI Visibility Index

Marketing without data is like driving with your eyes closed.

How do customers interact with my newly launched product?

How do I increase my employees' productivity?

How do I know if my marketing efforts are working?

We have just two words for you...Data analytics!

In this post, we will dive into this complex field and give you an idea:

How brands are using data analytics technology to improve their work processes

What's the Difference Between Data Science and Data Analysis?

How to Develop a Successful Data Analytics Strategy

Examples of How Organizations Benefit from Data Analytics

What Are the Main Types of Data Analytics?

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How Does AI in Social Listening and Media Monitoring Work?

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Best AI Tools for Public Relations: Complete 2026 Guide

Top AI Marketing Tools to Automate & Optimize Your Strategy

Digital 2026 Global Overview Report

Meltwater Added to Microsoft Marketplace for AI Apps and Agents

Social Media Statistics for China [Updated 2025]

Discover LLM-Driven Brand Perception with GenAI Lens

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Fitness Apps Brand AI Visibility Index

What Is Data Analytics? [Beginner’s Guide 2026]

What is AI in Influencer Marketing? (And How it Works)

How Does AI in Social Listening and Media Monitoring Work?

AI in Social Media Marketing

Best AI Tools for Public Relations: Complete 2026 Guide

Top AI Marketing Tools to Automate & Optimize Your Strategy

Digital 2026 Global Overview Report

Meltwater Added to Microsoft Marketplace for AI Apps and Agents

Social Media Statistics for China [Updated 2025]

Discover LLM-Driven Brand Perception with GenAI Lens

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